Table 7 - uploaded by Pavel Timonov
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Assessment of sex from femoral dimensions has been tried before in several populations. Studies conducted so far have demonstrated that populations differ from one another in size and proportion. The discriminant formulae developed for determining sex for one population group cannot be applied on another. This study establishes standards for determ...
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Sex determination based on discriminant function analysis of skeletal measurements is probably the most effective method for assessment of sex in archaeological and contemporary populations due to various reasons, but it also suffers from limitations such as population specifi city. In this paper standards for sex assessment from the femur and tibi...
Assessment of sex from femoral dimensions has been tried before in several populations. Studies conducted so far have demonstrated that populations differ from one another in size and proportion. The discriminant formulae developed for determining sex for one population group cannot be applied on another. This study establishes standards for determ...
Citations
... Marked differences in the range of 1.3-22.4% were observed in a cross-population study of sex estimation models from the long bones of the upper limbs [2]. Similarly, when sex estimation models of the femur were extrapolated from a Thai and Chinese to a Bulgarian population, considerable differences were observed [8]. This has led to some authors recommending the formulation of population-specific models for sex estimation [2]. ...
... There were considerable differences in mean ulna lengths between Ghanaians in this study and populations from Asia, Europe and South America but the differences were greater among the Japanese and the Koreans [18,30] as compared to the Europeans [28,29,32,33], South Americans [23] and other Asians [31]. Similarly, greater differences were observed in the mean femur length between Ghanaians in this study and populations from Asia [19][20][21][22]34], Europe and South America [8,19,23]. Osteological variations the demarking points (dP) and the sexual dimorphism index (Sdi) in the current study were compared with other population-specific studies. the dP was calculated as the mean of the male and female values. ...
... However, the performance of discriminant models from the femur on the holdout sample varied widely from the Japanese [17], the Turkish [19] and the Indian [20] models, which were all derived from skeletal samples. Poor outcomes from cross-testing population-specific sex estimation models from postcranial bones were also reported in a study by Timonov et al. [8] in Bulgaria. We, therefore, recommend more population-specific studies. ...
Sex estimation models form a vital part in Forensic human identification but they are usually population-specific. This study aimed to develop and test sex estimation models for a Ghanaian population using percutaneous lengths of the femur (FL) and ulna (UL). The study was cross-sectional from June to July 2020, involving
99 adults (male: 52, females: 47), aged between 19 and 31years.
The lengths of the femur and ulna were measured using standard
anthropometric techniques. All measurements were taken twice
from the left side and then averaged. The sample was randomly
divided into training (n=60) and holdout (n=39) samples before
been analysed using discriminant function analysis (DFA).
Cross-population studies were performed to test the reliability of
the models. Males had longer femur and ulna than females
(p<0.001). Sex estimation accuracies from all the models ranged
from 68.2% to 81.8% for males and 52.9% to 86.7% for females.
The standardized mean difference (SMD: Cohen’s d) by sample
type ranged from −0.19 to 3.08 (living samples), 0.19 to 4.73
(cadaveric samples) and 0.30 to 5.46 (skeletal samples). The SMD
by population type were: Africa, excluding Mixed or White ethnicities (d= −0.02 to 3.08), Asia (d=0.83 to 4.85) and Europe or the
Americas (d=0.30 to 3.38). When other population-specific models
were tested on the holdout sample, the difference in the average
sex estimation accuracy ranged from 0 to 25.6%. Sex estimation
models from the lengths of the femur and ulna are specific to a
the studied population and the type of sample used.
... On the other hand, the cross population testing of sex estimation methods on a different sample while controlling for the same variables in the original formulas resulted in promising results despite of being relatively lower in accuracy. [4,[20][21][22][23][24] The femur dimensions of target population might be close to those of the other populations from which the function was derived in addition to geographical, temporal proximity with or without similarities in the biological affinity. [19][20][21][22][23][24] Indian [20] and Thai [21] populations data when inputted into Chinese formula [22] resulted in classification accuracy from 71.3% to 87.1% in males and from 100% to 94.1% in females, respectively. ...
... [4,[20][21][22][23][24] The femur dimensions of target population might be close to those of the other populations from which the function was derived in addition to geographical, temporal proximity with or without similarities in the biological affinity. [19][20][21][22][23][24] Indian [20] and Thai [21] populations data when inputted into Chinese formula [22] resulted in classification accuracy from 71.3% to 87.1% in males and from 100% to 94.1% in females, respectively. Interestingly, the discriminate function (DF) of American black [25] when applied to Bulgarian data [24], satisfactory classification was attained 92.6% for males and 87.9% for females despite of being different ancestries and geographically distant populations. ...
... [19][20][21][22][23][24] Indian [20] and Thai [21] populations data when inputted into Chinese formula [22] resulted in classification accuracy from 71.3% to 87.1% in males and from 100% to 94.1% in females, respectively. Interestingly, the discriminate function (DF) of American black [25] when applied to Bulgarian data [24], satisfactory classification was attained 92.6% for males and 87.9% for females despite of being different ancestries and geographically distant populations. ...
Accurate and reliable methods of sex estimation are essential in forensic practice. In the literature, both the population based and non population specific standards are existing. In the present work, the summary statistics of 3 femoral standard measurements (joints and length dia meters) were collected from 13 published studies of modern populations. The metric data of each population were regenerated using truncated normal distribution approach. A simulated metapopulation database was constructed using the combined metric data of 2275 femur bones. Despite interpopulation differences, the calculation of stable non population specific discriminant functions (DF) was possible using the most discriminatory variables selected by stepwise analysis. The functions were tested on raw data of 6 populations which were obtained from authentic sources. The pooled DFs produced lower but comparable accuracies to the population specific functions using fewer number of variables. The total allocation accuracies of the temporally distant Terry coll ection did reach better than 90% in both American white and blacks while in the contemporary Turkish and Hispanic samples were more than 85%. In Asian populations, the total accuracies ranged from 69.7% to 84.9%. Nevertheless, raising the posterior probabi lity threshold to 0.95 increased the total allocation accuracies above 95% in all populations using the pooled populations function of femur joints diameters. This function permitted the classification of one third to more than half of the total sample siz e in each population which suggest a considerable practical value in estimating sex of unknown individuals without a priori recognition of population affinity.
... while mean maximum female femoral length in present study was similar to the valve in American whites and Californian sample. According to development of the general features of long bone size and shape depends on genetic factors while the manifestation of its characteristics depends on the mechanical environment 15 . Meera Jacob et al 16 calculated p value, the difference in mean maximum length in males and females was highly statistically significant (p<0.0001). ...
... Application of metric data from one population into the DFA derived from different population groups results in high classification error, and the results are also affected by large sex bias [36,37]. In a study designed to quantify the effect of applying Euro-American [38] and South African of European ancestry [39] standards to Australian population sample [40], classification accuracy was approximately the same in Australian sample as in target sample (e.g., 80-83 %). ...
... The effect of disregarding population specificity on the classification accuracy of DFA is often mentioned [25] but is rarely described for different parts of the skeleton. In recent publications, we found such studies only for crania from Western Australian and Indian populations [25,30] and in European populations for the clavicle [41], the calcaneus [37], and for the femur [36]. Recently, many authors have argued for the development and use of population-specific formulae for diverse parts of skeleton when metric data are used [25,30,35,[41][42][43][44][45]. ...
Forensic anthropology has developed classification techniques for sex estimation of unknown skeletal remains, for example population-specific discriminant function analyses. These methods were designed for populations that lived mostly in the late nineteenth and twentieth centuries. Their level of reliability or misclassification is important for practical use in today's forensic practice; it is, however, unknown. We addressed the question of what the likelihood of errors would be if population specificity of discriminant functions of the tibia were disregarded. Moreover, five classification functions in a Czech sample were proposed (accuracies 82.1-87.5 %, sex bias ranged from -1.3 to -5.4 %). We measured ten variables traditionally used for sex assessment of the tibia on a sample of 30 male and 26 female models from recent Czech population. To estimate the classification accuracy and error (misclassification) rates ignoring population specificity, we selected published classification functions of tibia for the Portuguese, south European, and the North American populations. These functions were applied on the dimensions of the Czech population. Comparing the classification success of the reference and the tested Czech sample showed that females from Czech population were significantly overestimated and mostly misclassified as males. Overall accuracy of sex assessment significantly decreased (53.6-69.7 %), sex bias -29.4-100 %, which is most probably caused by secular trend and the generally high variability of body size. Results indicate that the discriminant functions, developed for skeletal series representing geographically and chronologically diverse populations, are not applicable in current forensic investigations. Finally, implications and recommendations for future research are discussed.
... [4] Though there have been previous studies on sexual dimorphism in femur, it has been found that magnitude of sex related differences depends on the particular regional population. It is dependent on race, dietary habits, lifestyle, cultural practices, etc. [6,8] India is a land of diversity with different geographical and climatic zones. Hence, there is wide variation in anthropometric dimensions between different populations. ...
... Therefore, the method employed during this study appears to be reliable and reproducible. To verify the population specificity of the discriminant function equations, the Turkish population data were applied into the discriminant function formulas from other populations: Indian [26], Bulgarian [36], German [22] and South African [5] . Comparison has been made between the same four variables (VHD, FEB, MTD, FVDN) are used. ...
The identification of victims involved in mass fatality incidents has become an increasingly important issue nowadays, and identification of unknown individuals is an important aspect in criminal cases and Disaster Victim Identification scenarios. Therefore, the sex estimation is one of the most important biological attributes towards establishing personal identity. In addition, several studies have demonstrated that metric sex determination methods of the skeleton are population-specific due to variation in size and patterns of sexual dimorphism. Unfortunately, the modern Turkish population still lacks wide and representative population standards for identification. Previous research has shown that modern technologies, such as CT scanning appear to offer promising means for the establishment of new standards for contemporary populations. The main aim of this project is to examine the application of measurements taken from the femur in order to assess sex, as well as to contribute to the establishment of discriminant function equations for the Turkish population for forensic applications.
Refractive errors (RE) are commonly reported visual impairment problems worldwide. Previous clinical studies demonstrated age‐related changes in human eyes. We hypothesized that the binocular RE metrics including sphere and cylinder power, axis orientation, and interpupillary distance (IPD) can be used for forensic age estimation of an unknown individual. RE data of both eyes were collected from the clinical optometric exams and prescription glasses of 2027 Egyptian individuals aged between 2 to 93 years. The differences between age groups as well as sides, and sexual dimorphism were explored. Two modeling methods were compared: multiple and stepwise linear regression (LR) versus machine learning Regression Forest (RFM). Data were apportioned into training and test datasets with a ratio of 80/20. The results showed significant differences among the age groups in each eye for all variables. Stepwise LR improved the results over models based on the one‐sided lens due to selection of IPD in addition to the left and right axis, and left sphere as independent variables. For the RFM, the left axis and IPD were the most important features. RFM outperformed LR in terms of accuracy and root mean squared error (RMSE). The estimated age within ±10 years showed 81.4% accuracy rate and RMSE = 8.9 years versus 38.5% accuracy rate and RMSE = 17.99 years using RFM and stepwise LR, respectively, in the test set. The current study upholds the significance of the age‐related changes of refractive error in formulating alternative forensic age estimation models when standard methods are unavailable.
Objective:
The degree of sexual dimorphism in certain traits between males and females differ from one sample to another. Although trait differences by sex are often reported in bioanthropological research, few studies test for statistical significance or make raw data available. TestDimorph is the first R package dedicated to testing and comparing the degree of sexual dimorphism among different samples by leveraging summary statistics.
Materials and methods:
We provide two approaches of analysis of inter-sample differences in degree of sexual dimorphism: univariate and multivariate for two or more samples. The methods follow upon publications primarily from the AJBA. Within-sex size variability between samples is compared using one-way ANOVA followed by control for multiple pairwise comparisons. In addition, we compute the overlapping area between the density functions of two normal distributions from the mixture intersection index or the non-overlapping area using the dissimilarity index as well as Hedges' g with inferential support using the 95% confidence interval. Finally, we use a multivariate analysis of differences in patterning of sexual dimorphism between samples.
Results:
We demonstrate various results from applying TestDimorph functions to data supplied with the package.
Discussion:
The package has many features including functionality for working with summary statistics, simulating data from summary statistics, and the extraction of summary statistics from raw data, so that the entire analysis can be performed through the package.
Human skeletal variability is influenced by several factors, including genetics, environment, and socio-cultural background. Forensic methods being traditionally based on targeted reference groups, it is recognized that they are population-specific. Additionally, secular trends highly impact on the skeletal morphology, but the effect of outdated methods on forensic cases is not yet well documented. This paper compares the sexual dimorphism of femoral dimensions in two samples from the Czech population separated by 60 years in time (Pachner and the Prague National Museum Collections). Significant secular trends are present within this short span in both sexes and for most of the seven tested linear variables. The consequence of secular trends on sex determination is tested with logistic regression, and a decrease in reliability is systematically observed when using the older Czech sample on the 20th century sample, whichever the set of variables included. A model based on a recent Croatian sample provides a higher reliability on contemporaneous Czech individuals. These results imply that above population specificity, temporal consistency may be a major criteria to fulfil when applying forensic anthropology identification methods.
